This course reviews
current methods for object category recognition, dividing them into four
main areas: bag-of-words models; parts and structure models; discriminative
methods and combined recognition and segmentation. The emphasis will be on
the important general concepts rather than in depth coverage of contemporary
papers. The course is accompanied by extensive Matlab demos.

The 7 classes are: Airplane, Cars Rear, Face, Guitar, Leopard,
Motorbike, Wrist Watch. In each subdirectory, the labels are contained
within a Matlab file, Ground_Truth.mat. This has a tri-state label for
each image. 0 = Junk, 1 = Intermediate and 2 = Good Example. The
labeling was performed by an individual who has no knowledge of the algorithm.

Constellation Model. Code for
CVPR'03 and CVPR'05 papers.

I have code available
for distribution for both the CVPR'03 paper "Object
Class Recognition by Unsupervised Scale-Invariant Learning" and also the CVPR'05
paper "A Sparse Object Category Model for Efficient Learning and Exhaustive
Recognition". The CVPR'03 code is Linux only. The CVPR'05 code works under both
Windows and Linux and uses the VXL libraries. Please email
me if you would like the code.

Oxford
Robotics Reading Group on EM

Here are some
materials from the reading group I gave on EM in Oxford on 24/05/05.